Article from resourceful: Issue 12
Exploration, mining and processing companies require reliable data about the character and composition of mineral resources. What value do you think mineral characterisation delivers for these operations?
The value of mineral characterisation for the resources industry is undeniable, particularly when it is linked directly to metallurgical data (geometallurgy). It translates the traditional definition of mining blocks from grade and tonnes to value, such as the expected mineral recovery against operating costs.
A value-based mine model allows optimal mine scheduling to maximise profit as early as possible, optimises extraction efficiency and pro-actively manages problematic ore types in the processing plant.
Different processes require data that are fit for purpose with appropriate confidence levels. Sometimes this means that data with a high degree of analytical accuracy and precision is very important, such as indicator-mineral chemistry for exploration. Other times we need technologies that provide fast throughput and high volumes of data at an analytical accuracy that only need to provide reliable "estimates".
How does quality characterisation contribute to the bottom line for resource companies at various stages of the value chain?
The earlier the data are available the more value it adds. In the exploration phase, if quality indicator-mineral data – which is relatively cheap to collect – can confidently suggest that a target is substandard, companies can walk away before spending millions on drilling, or billions on plant and infrastructure building for a project that doesn’t deliver value.
In the development phase, quality orebody knowledge acquired before and during flowsheet design will inform the most appropriate processing options and highlight costly fatal flaws in design.
Once the plant is operational, mineral characterisation plays a more reactive role and the value becomes more incremental.
Think of it as the length of a spanner. The longer the handle the more torque you can apply to the bolt. The earlier mineral characterisation is done the bigger the monetary return.
Mineral characterisation covers a range of different techniques and technologies that provide an array of data and information. In the era of big data, what role does the expert play in translating this information into valuable, profitable decisions?
Experts play a crucial role in translating the data for decision-makers and need to take accountability for that translation process. The mineral characterisation expert is one step further removed from the decision-related pressure faced by the resource geologist, the mining engineer or processing plant superintendent. They are the ones that have more time and space to step outside the boundaries of pure mineral characterisation and understand the issue and how the data inform the issue.
For example, handing over a report to a flotation plant manager with a comment like "yesterday you lost 10 per cent recoverable copper and it looks like it was most likely a problem in the grinding circuit" is a lot more useful than "here are your chalcopyrite liberation plots from yesterday".
The resources sector invests significantly in innovation to increase productivity and ensure the industry is sustainable. Do you think innovation in mineral characterisation and analysis will help achieve these objectives?
Yes definitely, provided the data are available early enough. From a characterisation perspective, the more proactively (rather than reactively) you respond to an ore-related issue, the greater the productivity gains will be.
What technologies are exciting you most in the world of mineral characterisation?
Real-time online technologies with fast integration with other data from multiple sources and informative visualisation capability that allow a timely and confident response.
Do Australian suppliers of characterisation services adequately respond to the needs of the industry?
Some do, some don't. The most useful collaboration with suppliers of characterisation services is when there is a fundamental understanding of, and focus on, the ultimate business value and/or commercial pain points. This seems obvious but in my experience has not always been the case. Commercial focus and fundamental research are not mutually exclusive.
What are some future challenges for mineral characterisation?
Characterisation technologies are developing faster than we can solve the challenge of sample representivity.
How do we translate the interesting data we have for a teaspoon worth of dirt from a particular ore type, in to useful information for the truckloads of variably mixed ore we will mine?
This brings us back to big data again. The only solution I see to this issue is the integration and interpretation of multiple data sources at different scales in a multi-disciplinary collaborative environment. From the scale of the remote sensing fly-over right down to the forensic mineralogist sitting behind the scanning electron microscope.
What would be the growth opportunities for characterisation to support Australia’s resource sector?
Data fusion and data analytics technologies that allow an informed and timely response to ore properties and ore variability.
Lip service is often paid to the value of mineral characterisation in the resources sector, but in my opinion it is still not being used to full potential. This is because making a change in response to new information to an established model or process can be viewed as too daunting or too risky, no matter how convincing the data in that report on your desk.